This section evaluates the proposed approach and compares against state-of-the-art 6D pose tracking and estimation methods on two public benchmarks, the NOCS dataset [1]} and the YCBInEOAT dataset [2]}. Experiments are performed over diverse types of objects and various tracking scenarios (e.g., moving camera or moving objects). Both quantitative and qualitative results demonstrate that BundleTrack achieves comparable or even superior performance relative to alternatives, although it does not require instance or category-level 3D models. Concretely, no CAD models or training data from a 3D object database are used by BundleTrack. All experiments are conducted on a standard desktop with Intel Xeon(R) E5-1660 v3@3.00GHz processor and a single NVIDIA RTX 2080 Ti GPU.
